Kafka Interview Questions

With numerous job opportunities and career opportunities in Kafka, the popularity of Apache Kafka is skyrocketing. Furthermore, in this day and age, knowing Kafka is a fast track to success.

So, in this article, “Most Popular Kafka Interview Questions and Answers,” we have compiled a list of the most frequently asked Apache Kafka Interview Questions and Answers for both experienced and inexperienced Kafka Technology professionals.

As a result, if you want to prepare for an Apache Kafka interview, this is the place to be. This will assist you in acing your Kafka interview.

Best kafka interview question and Answers:

Well here's a list of the most popular Kafka Interview Questions and Answers that any Interviewer may ask. So, continue reading until the end of the article “Kafka Interview Questions” to ace your interview on the first try.

Kafka interview questions for freshers:

Most Frequently asked interview Questions 

1.What exactly is Apache Kafka?

Apache's response Kafka is an open source publish-subscribe message broker application. Scala was used to create this messaging application. This project was essentially initiated by the Apache software. Kafka's design pattern is primarily based on transactional logs.

2. What are the components of kafka?

The components of kafka are topic, producer, consumer and brokers.

3.Explain the function of the offset.

The messages in the partitions are assigned a sequential ID number, which we refer to as an offset. So, we use these offsets to uniquely identify each message in the partition.

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4.What exactly is a Consumer Group?

Apache Kafka invented the concept of Consumer Groups. Every Kafka consumer group is made up of one or more consumers who consume a set of subscribed topics together.

5.What is the ZooKeeper's role in Kafka?

Apache's response Kafka is a distributed system designed to work with Zookeeper. However, Zookeeper's primary role in this context is to establish coordination between different nodes in a cluster. However, because it works as a periodically commit offset, we also use Zookeeper to recover from previously committed offsets if any node fails.

6.Is it possible to use Kafka in the absence of ZooKeeper?

Because it is impossible to connect directly to the Kafka server without using Zookeeper, the answer is no. If ZooKeeper fails, it is impossible to service any client request.

7.What do you know about Kafka's Partition?

There are only a few partitions available in every Kafka broker. And, in this case, each Kafka partition can be either a leader or a replica of a topic.

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8.What are the main Kafka APIs?

Apache Kafka has four main APIs:

  • API for the producer
  • API for Consumers 
  • Streams API
  • API for Connectors

9.What are consumers?

Kafka Consumer primarily subscribes to a topic(s), as well as reads and processes messages from the topic (s). Furthermore, by naming a consumer group, consumers label themselves.

In other words, each record published to a topic is delivered to one consumer instance within each subscribing consumer group. Ascertain that Consumer instances can exist in separate processes or on separate machines.

10.What are your options with Kafka?

It can perform in a variety of ways, including: >> To transmit data between two systems, we can build a real-time stream of data pipelines with it; >> We can also build a real-time streaming platform with Kafka that can actually react to the data.

11.What is the purpose of the Kafka cluster's retention period?

The retention period, on the other hand, keeps all published records within the Kafka cluster. It makes no distinction between whether or not they have been consumed. Furthermore, the records can be discarded by configuring the retention period. And it has the added benefit of freeing up some space.

12.What are the different types of traditional message transfer methods?

There are two basic methods of traditional message transfer, which are as follows:

Queuing is a method in which a pool of consumers reads a message from the server, and each message is delivered to one of them.

Publish-Subscribe: Messages are broadcast to all consumers in Publish-Subscribe.

Kafka interview questions for Experienced:

1.Why is Kafka technology important to employ?

Kafka has some advantages that make it worthwhile to use:

  • High-throughput
    Kafka does not require any large hardware because it can handle high-velocity and high-volume data. Furthermore, it can handle message throughput of thousands of messages per second.
  • Latency is low.
    Kafka can easily handle these messages with the millisecond latency required by the majority of the new use cases.
  • Fault-Tolerant
    Within a cluster, Kafka is resilient to node/machine failure.
  • Durability
    Messages are never lost because Kafka supports message replication. It is one of the factors that contribute to durability.
  • Scalability
    By adding additional nodes, Kafka can be scaled-out without causing any downtime.

2.What ensures the server's load balancing in Kafka?

Because the Leader's primary role is to perform all read and write requests for the partition, Followers passively replicate the Leader.As a result, if the Leader fails, one of the Followers takes over as Leader. Essentially, this entire process ensures that the servers' load is balanced.

3.What are the roles of Replicas and the ISR?

Replicas is essentially a list of nodes that replicate the log. Especially for a specific partition. They are, however, regardless of whether they play the role of Leader.

Furthermore, ISR stands for In-Sync Replicas. ISR is defined as a set of message replicas that are synced to the leaders.

4.Why are Replications so important in Kafka?

We can be certain that published messages are not lost and can be consumed in the event of a machine error, a program error, or frequent software upgrades thanks to replication.

5.What does it mean if a Replica stays out of the ISR for an extended period of time?

Simply put, it means that the Follower cannot retrieve data as quickly as the Leader.

6. When does a QueueFullException occur in the Producer?

When the Kafka Producer attempts to send messages at a rate that the Broker is unable to handle, a QueueFullException is typically thrown. However, because the Producer does not block, users will need to add enough brokers to collaboratively handle the increased load.

7. Describe the function of the Kafka Producer API.

Producer API refers to an API that allows an application to publish a stream of records to one or more Kafka topics.

8. What is the primary distinction between Kafka and Flume?

The main distinctions between Kafka and Flume are as follows:

  • Tool classifications
    Apache Kafka– Because Kafka is a general-purpose tool, it can be used by both multiple producers and consumers.Apache Flume– Flume, on the other hand, is regarded as a specialized tool for specific applications.
  • Feature of replication:Apache Kafka– Kafka is capable of replicating events.Flume, on the other hand, does not replicate the events.

9.Is Apache Kafka a platform for distributed streaming? If so, what can you do with it?

Without a doubt, Kafka is a streaming platform. It can assist in the following ways:


To easily push records

Furthermore, it can store a large number of records without causing any storage issues.

Furthermore, it can process records as they arrive.

10.What is the maximum size of a message that Kafka can accept?

The maximum size of a message that Kafka can receive is approximately 1000000 bytes.

11.What is the purpose of the Streams API?

Streams API is an API that allows an application to act as a stream processor by consuming an input stream from one or more topics and producing an output stream to one or more output topics, as well as effectively transforming the input streams to output streams.

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12.What is your explanation, Producer?

Producers' primary responsibility is to publish data on topics of their choosing. Its primary responsibility is to select the record to assign to the partition within the topic.

13.Describe how to tune Kafka for maximum performance.

So, one way to tune Apache Kafka is to tune its various components:

  • Kafka Tuning Producers
  • Kafka BrokersTuning
  • Tuning Kafka Consumers

Conclusion:

Hence, you now know the best Kafka Interview Questions and Answers.

Furthermore, if you have recently attended any Kafka interviews, we would appreciate it if you could add more Kafka Interview Questions in the comments section. I hope this helps you get through the Kafka interview.

1) Define Kafka's Geo-Replication.

Kafka Interview Questions for Advanced

Ans. In Kafka, the Geo-replication feature helps in data replication throughout various data and clusters. Kafka MirrorMaker is the ideal tool that enables geo-replication for groups. By using this tool, you can replicate (copy) messages across various cloud data centers. 

2) Define the terms

Ans. In Kafka, each partition contains a single server that performs as a Leader, and one or more servers act as Follower. Here, a Leader is responsible for executing all the read and write activities in the partition. But the Follower is in charge of passively replicating the Leader. To balance the server's load, one of the Followers takes over the leadership in case the Leader fails.

3) How do you configure a Log cleaner?

Ans. A Log Cleaner is, by default, active and begins the pool of cleaning threads. To enable a Log cleaning on a particular topic, it needs an addition of: log.cleanup.policy=compact. We can finish it using the command called “modify topic command” or at the time of the topic creation process. 

4) What is meant by Kafka's Log Anatomy?

Ans. Log Anatomy is another way to see (view) a partition where a data source writes messages to the Log. It allows one or more consumers to read the data from the Log whenever required. Further, the Log anatomy states that a data source can write a log, and consumers read the same at various offsets in parallel. 

5) What is

Ans. Kafka is useful as a multi-tenant solution that allows the configuration of different topics for data consumption or production. 

6) What is fault tolerance, and how does Kafka provide fault tolerance?

Ans. In Kafka, data is stored in different cluster nodes as Kafka is a distributed system. There is a strong chance of failing one or more cluster nodes Fault tolerance refers to the system's data being protected and available upon the failure of the cluster nodes. Further, Kafka offers fault tolerance by saving copies of the partitions.

7) Define the use of Connector API in Kafka.

Ans. In Kafka, the Connector API enables the managing and development of repeatable producers that connect Kafka subjects to the data systems. 

8) Define a broker in Kafka.

Ans. The broker is a server within the Kafka cluster in Kafka. Brokers help manage a cluster using Apache ZooKeeper. Each broker holds a unique ID and can be the owner of more than one topic's Log division. Further, each broker has more than one partition, and they are stateless.

9) How do you start a Kafka Server?

Ans. Before you start the Kafka Server, you need to start the ZooKeeper. First, you should download the new version of KafkaYou need to enter a command in the terminal to start the ZooKeeper a. Once it starts running, you can start the Kafka Server. 

10) What is the role of Producer API in Kafka?

Ans. The Producer API in Kafka allows applications to publish data streams to the Kafka cluster. 

11) Define serialization and deserialization in Kafka.

Ans. In Kafka, the serialization process helps convert objects into streams of bytes valid for transmission. Kafka stores and transfers the bytes of arrays in its queue system. On the other hand, deserialization is the opposite of serialization, which allows for the conversion of bytes of arrays into the required data type. 

12) What are the broker configuration files?

Ans. The most crucial broker configuration files include- Log.dirs, broker.id, zookeeper. connect.

13) Define Kafka monitoring use cases.

Ans. The following are the various use cases of Kafka monitoring.:-

  • Monitoring threads and usage of JVM - Kafka mainly uses a Java garbage collector to free up the memory and ensure it runs frequently. It makes the Kafka cluster more active.
  • Tracking System Resources - It helps keep track of all the system resources, including memory, CPU, and disk space usage over time.
  • Keep tracking of the broker, controller, and replication data to alter the status of replicas and partitions as per need. 
  • We can resolve performance issues by identifying performance issues and apps causing extreme demand. 

14) What are the different ways that Kafka imposes security?

Ans. The following are the different ways through which Kafka imposes security.:-

  • Encryption
  • Authentication
  • Authorization

Encryption - The communications between the Kafka broker and its clients are highly encrypted, which secures data from the interruptions of other clients. Further, messages are also shareable with proper encryption between the components.

Authentication - Applications that use Kafka brokers need authentication before they connect with Kafka. Only approved apps can send or receive messages in this case. These authorized apps will include a unique ID and password to locate themselves quickly.

Authorization - The authorization process executes after the authentication process. After its validation, a client can publish or consume messages. The permission limits the app's writing access to prevent data impurity.

15) What is meant by Kafka MirrorMaker?

Ans. Kafka MirrorMaker is a discrete helpful tool to copy data from one Apache Kafka to another. It reads the data from the native cluster topics and writes it to the target cluster with the same name. 

16) What is Consumer Lag in Kafka?

Ans. A consumer lag in Kafka shows how much delay or lag between writing a message and its consumption. It is the difference between the highest offset and the existing offset of the consumer. 

17) What does Kafka Cluster mean, and what are its various benefits?

Ans. Kafka Cluster is a collection of brokers, partitions, and topics. Even if we expand the cluster, it has zero downtime. The primary objective of the Kafka cluster is to distribute the workloads between the partitions and replicas equally. Further, the Kafka Cluster Architecture consists of different components such as broker, topics, producers, consumers, and ZooKeeper.

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18) Explain how Kafka works?

Ans. Kafka application works in the following order:-

  • Producers regularly send messages on a topic.
  • Kafka Broker stores all the messages available in the partitions set for the given topic.
  • Then Kafka ensures that if the producer publishes the two messages, a consumer should accept both. 
  • Later the consumers drag the messages from the issued topic.
  • Kafka pushes the offset value towards the ZooKeeper after the consumers absorb the given topic.
  • Consumers regularly send the signal to Kafka approximately every 100ms and wait for the messages. 
  • Later the consumer sends the acceptance when a message is received.
  • When Kafka gets the acceptance, it alters the offset value to the new value and sends it to the Zookeeper. Thus, Zookeeper upkeeps this value so that consumers can read the upcoming message exactly, even during server repels.
  • Hence, this flow continues until the sent request is live.

19) Define the various operations of Kafka.

Ans. The following are the various operations of Kafka.:-

  • Adding & Removing Kafka Topics
  • Modifying the Kafka Topics
  • Copying data between different Kafka Clusters
  • Locating the exact status of the Kafka Consumer
  • Expanding Your Kafka Cluster
  • Migration of Data Automatically
  • Retiring Servers
  • Data Centers

20) Name the different Kafka System Tools.

Ans. The following are the different types of Kafka System Tools.:-

  • Mirror Maker
  • Consumer Offset Checker
  • Kafka Migration Tool

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Gayathri
Gayathri
Research Analyst
As a senior Technical Content Writer for HKR Trainings, Gayathri has a good comprehension of the present technical innovations, which incorporates perspectives like Business Intelligence and Analytics. She conveys advanced technical ideas precisely and vividly, as conceivable to the target group, guaranteeing that the content is available to clients. She writes qualitative content in the field of Data Warehousing & ETL, Big Data Analytics, and ERP Tools. Connect me on LinkedIn.